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Recent Alerts

recent_alerts
Read-onlyIdempotent

Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp). Set mark_read:true to flag returned events read so the next call only shows newer ones. Polls work fine; the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional — filter to one subscription type.
limitNoMax events to return (1-200, default 50).
sinceNoOptional ISO timestamp — return events fired_at >= this time.
mark_readNoFlag the returned events read in the same call (default false).
unread_onlyNoReturn only events where read_at is null (default false).

TDQS

B3.3/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description states that mark_read:true flags events as read, which modifies the feed state. This contradicts the annotation readOnlyHint=true, which implies no state mutation. The description does disclose this behavior, but the contradiction to annotations is a serious inconsistency that undermines trust.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph of five sentences, front-loaded with the core purpose. It is concise and each sentence adds value (purpose, return fields, filtering options, mark_read effect, alternative endpoint). Minor room for improvement in structuring with bullet points.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given five optional parameters and no output schema, the description covers essential return fields, filtering, mark_read state change, and provides an alternative access method. It is sufficiently complete for an agent to use the tool effectively, though it could briefly mention pagination or limit behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for all five parameters. The description adds usage context (e.g., 'e.g. "sec_8k"' for type) but does not introduce new meaning beyond the schema. Baseline 3 is appropriate as the description merely reinforces existing schema information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description begins with 'Pull fired events from your subscription feed,' clearly stating the verb (pull) and resource (fired events). It further enumerates return fields (source, citation_uri, raw payload). However, it does not explicitly differentiate from sibling tools like 'recent_changes' or 'validate_claim', so it lacks explicit sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on filtering by type and since, and on using mark_read to control read state for subsequent calls. It also mentions that polling works and provides an alternative endpoint for scripts/dashboards. However, it does not state when not to use this tool or suggest alternative tools for different use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.4/5.0
Disambiguation3/5

Many tools have distinct purposes, but there is notable overlap between ask_pipeworx, ask_pipeworx_grounded, and deep_research, all serving data retrieval. Similarly, the Polymarket betting tools (bet_research, polymarket_arbitrage, polymarket_edges, etc.) share a domain, causing potential confusion for an agent.

Naming Consistency2/5

Tool names follow no consistent pattern: snake_case (ai_visibility_check), camelCase-like (bet_research, compare_entities), and noun-first (entity_profile, recent_changes) are mixed. The lack of a uniform verb_noun or other convention makes it harder to predict tool names.

Tool Count2/5

35 tools is excessive for a server named 'Osrm,' which suggests a focused routing engine. The actual tool set spans routing, data query, betting, entity resolution, and memory, indicating an overbroad scope that dilutes coherence.

Completeness3/5

The data query and betting tools are relatively comprehensive, but the routing side is minimal (missing isochrones, alternative routes). Gaps exist in general web search and coverage of other prediction markets. The server doesn't fully cover either the implied routing domain or the broader data/betting domain.